def tesla(self):
if not self.position:
if self.high[0] < 900:
if volatility(self, self.sma_1, 1, 1):
self.log(
'Buy attempt :: ref -- (#1) < 900 %.2f, sma[0] :%.2f, sma[-1] :%.2f'
% (self.high[0], self.sma_1[0], self.sma_1[-1]))
self.order = self.buy(size=1, price=self.high[0])
if self.high[0] > 900:
if volatility(self, self.sma_1, 1, 1):
self.log('Buy attempt :: ref -- (##### > 900 ')
self.order = self.buy(size=1, price=self.high[0])
if self.sma_10[0] > 3:
self.log('Buying for sma 10')
self.order = self.buy(price=self.high[0])
if self.position:
if len(self.bought) > 5:
pass
for i in self.bought:
if self.sma_10[0] > 3:
print('SMA 10 ---> ')
self.log(f'Buying for sma 10 {self.high[0]}')
self.order = self.buy(price=self.high[0])
if i < 500:
if i < 300:
# SELL COMMAND FOR LESS THEN 300
if (self.high[-1] - i) > 20:
self.log('SELL CREATE < 200 , %.2f' %
self.dataclose[0])
self.order = self.sell()
self.bought.remove(i)
# BUY COMMAND FOR LESS THAN 300
if (self.sma_1[0] - self.sma_1[-2]) > 1:
self.log(
'Buy attempt :: ref -- (#2) < 800 %.2f' %
self.high[0])
self.order = self.buy(size=1,
price=self.high[0])
# ------------------------------------------------------------------::
# BUY COMMAND FOR LESS THEN 500
else:
if (i - self.high[-1]) > 80: # greater then 300
self.log(
'Buy attempted with possesion > 300 already %.2f'
% self.high[0])
self.order = self.buy(size=1,
price=(i -
self.high[-1]))
# SELL COMMAND FOR LESS THEN 500
# IF PRICE DIFFERS BY 50 THEN BUY
if (self.high[0] - i) > 50:
self.log('SELL CREATE < 500 , %.2f' %
self.dataclose[0])
self.order = self.sell()
self.bought.remove(i)
# ------------------------------------------------------------------::
# IF I IS GREATER THEN 500
elif i > 500:
# IF VOLATILITY DIFFERENCE IS GREATER THEN 1.5
if (self.sma_10[0] - self.sma_10[-2]) > 1.5:
# THE STOCK IS SO VOLATILE THAT I WILL BUY SHARE EXTREMELY LOW BECAUSE ITS MOVING
if (i - self.high[-1]) > 200:
# BUY IF A THE HIGH IS 200 LOWER THEN AN ALREADY OBTAINED POSITION
self.log(
'THE MARKET IS VERY VOLATILE --BUY-- %.2f'
% self.high[0])
self.order = self.buy()
# ------------------------------------------------------------------::
# BUY COMMAND FOR GREATER THAN 500
if (i - self.high[-1]) > 100:
# self.log('Buy attempted with possesion > 500 already %.2f' % self.high[0])
self.order = self.buy()
# SELL COMMAND FOR GREATER THAN 500
if (self.high[0] - i) > 100:
# print(f'High: {self.high[0]}, i-value: {i}')
self.log(
'SELL CREATE:: REF -- (#3), High: %.2f, i : %.2f' %
(self.dataclose[0], i))
self.order = self.sell(size=1, price=(self.high[0]))
self.bought.remove(i)
if self.high[0] > 900:
if (self.sma_1[0] - self.sma_1[-1]) > 1:
self.log('Buy attempt ~ ref > 900)')
self.order = self.buy(size=1, price=self.high[0])
from black_scholes_model import * import bopm ### # Parameters symbol = 'qcom' strikePrice =50; daysToExp = 6; riskFreeRate = 0.15; ### data = HistoricalDataObj() # Use annual volatility. data.initialize(symbol,365,1,1, 'yahoo'); spotPrice = data.vClose[-1:]; vola = volatility(data.vClose, 252); bopmVal = bopm.bopm(spotPrice, strikePrice, daysToExp, riskFreeRate,vola) bsmVal = bsm(spotPrice, strikePrice, daysToExp, riskFreeRate, vola) print vola print bopmVal; print bsmVal
# Distributed under the GPL license Version 3.0 ( See accompanying file
# License_ or copy at http://code.google.com/p/finance-py/LICENSE)
################################################################################
## include source path
import sys
sys.path.append("../src/")
from historical_data_obj import *
from volatility import *
import matplotlib.pyplot as plt
data = HistoricalDataObj()
data.initialize("bp", 365)
print volatility(data.vClose)
# current minus the previous
delta = data.vClose[1:] - data.vClose[:-1]
deltaP = delta / data.vClose[1:] * 100
deltaLn = log(data.vClose[1:] / data.vClose[:-1])
v = std(deltaLn)
# there are 252 trading days in any given year
v2 = v / sqrt(1.0 / 252.0)
print (v) * 100
print (v2) * 100
plt.hist(deltaLn * 100)
plt.show()
# http://code.google.com/p/finance-py/
# Distributed under the GPL license Version 3.0 ( See accompanying file
# License_ or copy at http://code.google.com/p/finance-py/LICENSE)
################################################################################
## include source path
import sys
sys.path.append("../src/")
from historical_data_obj import *
from volatility import *
import matplotlib.pyplot as plt
data = HistoricalDataObj()
data.initialize("bp",365);
print volatility(data.vClose)
# current minus the previous
delta = data.vClose[1:] - data.vClose[:-1] ;
deltaP = delta / data.vClose[1:] * 100;
deltaLn = log(data.vClose[1:] /data.vClose[:-1] );
v = std(deltaLn) ;
#there are 252 trading days in any given year
v2 = v / sqrt(1.0/252.0);
print(v) * 100
print(v2) * 100
plt.hist(deltaLn * 100)
sys.path.append("../src/")
from historical_data_obj import *
from volatility import *
from black_scholes_model import *
import bopm
###
# Parameters
symbol = 'qcom'
strikePrice = 50
daysToExp = 6
riskFreeRate = 0.15
###
data = HistoricalDataObj()
# Use annual volatility.
data.initialize(symbol, 365, 1, 1, 'yahoo')
spotPrice = data.vClose[-1:]
vola = volatility(data.vClose, 252)
bopmVal = bopm.bopm(spotPrice, strikePrice, daysToExp, riskFreeRate, vola)
bsmVal = bsm(spotPrice, strikePrice, daysToExp, riskFreeRate, vola)
print vola
print bopmVal
print bsmVal
